Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course but also emphasizes stochastic modeling including Markov chains birth-death processes and reliability models. Unlike most undergraduate-level probability texts the book also focuses on increasingly important areas such as martingales classification of dependency structures and risk evaluation. Numerous examples exercises and models using real-world data demonstrate the practical possibilities and restrictions of different approaches and help students grasp general concepts and theoretical results. The text is suitable for majors in mathematics and statistics as well as majors in computer science economics finance and physics. The author offers two explicit options to teaching the material which is reflected in routes designated by special roadside markers. The first route contains basic self-contained material for a one-semester course. The second provides a more complete exposition for a two-semester course or self-study.|Probability and Stochastic Modeling | Mathematics
